Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use iproskurina/xtc2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iproskurina/xtc2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iproskurina/xtc2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iproskurina/xtc2") model = AutoModelForSequenceClassification.from_pretrained("iproskurina/xtc2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from iproskurina/xtc2: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/iproskurina/xtc2/resolve/main/training_args.bin
- Command line
-
hf download hf://iproskurina/xtc2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/iproskurina/xtc2/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- a39f476833ca661c0bb593876e99a71062567670849e4b80c9aee2a6a307afd6
- Size of remote file:
- 5.11 kB
- SHA256:
- 30e99e4b57d516c4849bd833c24fb2477c57dbfbb66f0e4a73e5cf750ee51060
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